Using whole genome sequencing to investigate transmission in a multi-host system: bovine tuberculosis in New Zealand

Joseph Crispell, Ruth N. Zadoks, Simon R. Harris, Brent Paterson, Desmond M. Collins, Geoffrey W. de-Lisle, Paul Livingstone, Mark A. Neill, Roman Biek, Samantha J. Lycett, Rowland R. Kao, Marian Price-Carter

Bovine tuberculosis (bTB), caused by Mycobacterium bovis, is an important livestock disease raising public health and economic concerns around the world. In New Zealand, a number of wildlife species are implicated in the spread and persistence of bTB in cattle populations, most notably the brushtail possum (Trichosurus vulpecula). Whole Genome Sequenced (WGS) M. bovis isolates sourced from infected cattle and wildlife across New Zealand were analysed. Bayesian phylogenetic analyses were conducted to estimate the substitution rate of the sampled population and investigate the role of wildlife. In addition, the utility of WGS was examined with a view to these methods being incorporated into routine bTB surveillance. A high rate of exchange was evident between the sampled wildlife and cattle populations but directional estimates of inter-species transmission were sensitive to the sampling strategy employed. A relatively high substitution rate was estimated, this, in combination with a strong spatial signature and a good agreement to previous typing methods, acts to endorse WGS as a typing tool. In agreement with the current knowledge of bTB in New Zealand, transmission of M. bovis between cattle and wildlife was evident. Without direction, these estimates are less informative but taken in conjunction with the low prevalence of bTB in New Zealand's cattle population it is likely that, currently, wildlife populations are acting as the main bTB reservoir. Wildlife should therefore continue to be targeted if bTB is to be eradicated from New Zealand. WGS will be a considerable aid to bTB eradication by greatly improving the discriminatory power of molecular typing data. The substitution rates estimated here will be an important part of epidemiological investigations using WGS data.